Our vision is to have screening covering all cancers, available to everyone, everywhere.
Are you interested in expanding your career through experience and exposure, all the while supporting a mission that seeks to enable screening covering all cancers to be available to everyone, everywhere? If so, then Tumour Trace may be the place you.
Tumour Trace uses a patented Opto-Magnetic Imaging Spectroscopy (OMIS) methodology that delivers objective results, faster, at less cost and more accurately than existing methodology. Using our technology, results can be available either at the point of the test or in the laboratory. We have been developing the Opto-Magnetic Imaging Spectroscopy (OMIS) methodology for several years and have undertaken a number of successful validation trials in the UK, Serbia and India with cervical, bowel, prostate and oral cancers.
We are passionate about what we do and we live and breathe different perspectives; we are curious about the world, accepting of each other, and well aware that the more ideas, backgrounds, opinions, and experiences we bring to our work, the stronger that work will be. Just as you would invest your time and hard work into Tumour Trace and its vision, we will invest back into through enriching professional experiences and high-quality learning and development opportunities. We want you to bring your whole self to work and for you to have meaningful connections with your coworkers, customers, and communities, while providing the best products, systems, and technologies to screen and diagnose cancers.
Tumour Trace is committed to hiring and retaining a diverse workforce. We are proud to be an equal opportunity employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class.
Tumour Trace seeks qualified candidates to serve as Biostatisticians in support of the Device and Statistical Learning Algorithms, and Clinical Studies teams. Successful candidates will have a strong background in statistics, including advanced statistical methodologies such as statistical learning and the ability to use these methodologies to classify diagnostic datasets.
Tumour Trace seeks qualified candidates to serve as Senior Software Engineers in support of the Device and Statistical Learning Algorithms team. Successful candidates will have a strong background in statistics, including advanced statistical methodologies such as statistical learning and the ability to use these methodologies to classify diagnostic datasets.